Tag Archives: 2018

INSPIRE Conference 2018

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The 2018 edition of the INSPIRE conference will take place in Antwerp, Belgium, 18-21 September. The motto of this years’ event is INSPIRE users: Make it work together!

The European INSPIRE Directive leads to a digital highway for sharing information on Europe’s environment. Member states are rapidly extending this network to reach all levels of government and application areas beyond the environment. Now that we have this essential European facility in place, we can exploit it to the full to support the digital transformation of European society.

The call for submissions is organised in 3 strands:

  1. INSPIRE the Users: In this strand special attention goes to inspiring the usage and users of INSPIRE. Both public and private parties are invited to share their experiences with creating applications that benefit from INSPIRE.
  2. Doing it Together: This strand is dedicated to ‘cooperation’. We are looking for examples where the cooperation between public and/or private sector organisations and programmes has been successfully developed to support the implementation of INSPIRE.
  3. Making it work: The strand adressess a more technical approach to ‘make it work’. We are calling for submissions where implementation issues have been identified and where the source of the problems has been – or needs to be – addressed (e.g. Simplifications encoding, Automatisations, quality assessment, etc.).

The call for submissions to the 2018 INSPIRE conference is now open: come and be part of this European success story!

https://inspire.ec.europa.eu/conference2018

TEAM 11: To Determine Fertilization Timing

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TEAM LEADER: Karl Gutbrod

 

PROJECT IDEA: A common problem of farmer relates to the decision when and where to fertilize the soil in relation to a given crop stage, weather conditions or field topography. With this project idea we want to prepare for a potential user a set of tools helping him to decide about the feasibility and  rentability of going to the field and fertilize given a current weather and soil conditions in given relief and potentially also given a current crop stage.

Decision criteria are:

  • is nitrogen fertilisation useful  in that area (land use map) – not in forest, water
  • is nitrogen fertilisation permitted in that area (optional: map of water catchment areas, seasonal restrictions, protected areas)
  • is the crop at the right stage (Satellite maps: is the crop in a phenological phase that requires fertilizer? + photographs acquired from the smartphone (both optional))
  • is the soil not too wet to apply fertilizer and drive with a tractor (soil type and moisture ).

TEST CASE:

  • multiple corn fields in Austria

DATASETS:

  • Open land use map
  • Crop growth incrementation from Sentinel-2
  • Soil type
  • Climate: rainfall, wind.., as well as historical weather data
  • Soil moisture
  • topography

TEAM 6: Cloud Version of SensLog

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TEAM LEADER: Ondřej Kaas

PROJECT IDEA: New version of SensLog was implemented during last months. This new version is more oriented on SensLog deployment in the cloud environment. New SensLog version is based on modern frameworks and with emphasize on real time processing.  The project is focused on testing of deployment of new SensLog and testing of API.

TEAM 4: REST API from Traffic Modelling

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TEAM LEADER: František Kolovský/University of West Bohemia

PROJECT IDEA: The goal of the project is developing REST API for the traffic modeling. The traffic modeling will be provided as a service via API. The backend of the API will be based on Python programing language using Flask framework. The final API should be ensured complete data, account and modelling management for transport modelling for a city area. The API will be used by Javascript frontend application.

The computing of the traffic will be ensured by using Apache Spark with JobServer (REST API for Apache). PostgreSQL with PostGIS extension will be used for data storage. OpenTransportMap is a suitable data source for creating road network for modelling.

TEAM 3: Big Data for Fishery

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TEAM LEADER: Karel Jedlička/University of West Bohemia

PROJECT IDEA: The main aim is to provide an easy to use web map application (based on HS Layers NG technology), which will help users (fleet manager, ship manager, …?) in decision making. Can be similar to https://www.windy.com/, but fed with fishery-related data and data from earth observation and meteorological forecast

The application will provide:

    • Several spatial data layers to create a custom map mashups:
      • Data from satellites (the way of visualisation will be defined for each layer) – Spacebel
        • Wind speed
        • Wind direction
        • Sea temperature
        • Chlorophyll
        • Temperature
        • Turbidity
        • …
      • Data from weather forecast (there meteo comp. As a partner of DataBio, MeteoBlue API)
        • Wind speed
        • Wind direction
        • ….
      • Other relevant data
        • Different management divisions (e.g. economic zones, large ecosystems and other)
        • …
      • Data about position of tuna fish species (both actually tracked and forecasted by a probabilistic model)
        • Including the probability in the case of forecasted data (by color saturation)
      • Data for ship routing
        • Visualise alternative routes with attributes of estimated fuel consumption and risk (by combination of route color and thickness or by detailed report when user click)
  • Challenge: provide a web interface to set up the start and end point of the route, then recalculate the route instantly to consider ship decisions
  • Dynamic visualisation of the data showing (a time slider will control, what is visualized):
    • Real time (=actual day) situation
    • Forecast (for how long?)
    • Historic data (just for fleet manager?) – an advanced visualization by WebGlayer can be prepared that allows not only visualization, but also basic analytics

The nature of the data is dynamics – all the data are changing in a half day period the most but each layer independently.

The map application will visualize data in various scales/levels of detail/granularity, but the initial granularity will be based on approx. 25 x 50 km (0.5 or 0.25 degrees) cells.

TEAM 2: Albatross

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TEAM LEADER: Christian Zinke zinke(at)infai.org

TEAM MEMBERS: Stephan Bischoff, Jörg Schließer

PROJECT IDEA: Exploratory Data Visualisation
The idea is to gather and deploy more datasets into Albatross. If possible we will connect SenseLog with Albatross in order to process and analyse the IoT data. Further, we will implement more forecasting models into Albatross.

TEAM 1: Using Time Series of Sentinel 2 and LPIS Data for Crop Detection

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TEAM LEADER: Vojtěch Lukas vojtech.lukas(at)mendelu.cz

TEAM MEMBERS: we are waiting for you …

PROJECT IDEA: Our idea is to combine time series of Sentinel 2 data from different year period in combination with Land Parcel Information System for detection of crops. The goal is not to have only classification of single pixels, but all parcels. We will offer crop rotation data from one large scale farm, LPIS data and time series. The task is to define best time periods for selections of single crops on the base of multi-temporal statistic. The outputs we expect are detection of parcels with more crops and detection of basic group of crops.
We are looking for people for our time to play with us with this data. We don’t expect necessary web publishing of this data, focus is more on methodology.